From 0497f918f457004149362198708d55cda494e8a9 Mon Sep 17 00:00:00 2001 From: Xavier Raynaud Date: Fri, 20 Dec 2024 14:59:03 +0100 Subject: [PATCH] more in documentation --- .../publishedExamples/runBatteryP2D.png | Bin 2464 -> 1206 bytes .../publishedExamples/runBatteryP2D_01.png | Bin 13773 -> 25971 bytes .../publishedExamples/runBatteryP3D.png | Bin 2810 -> 0 bytes .../publishedExamples/runBatteryP3D_01.png | Bin 30737 -> 0 bytes .../publishedExamples/runGasSupply.png | Bin 3073 -> 1281 bytes .../publishedExamples/runGasSupply_01.png | Bin 8506 -> 18066 bytes .../publishedExamples/runGasSupply_02.png | Bin 8534 -> 18187 bytes .../publishedExamples/runGasSupply_03.png | Bin 8555 -> 18301 bytes .../publishedExamples/runGasSupply_04.png | Bin 11330 -> 18617 bytes .../publishedExamples/runGasSupply_05.png | Bin 20404 -> 47352 bytes .../publishedExamples/runGasSupply_06.png | Bin 18867 -> 26873 bytes .../publishedExamples/runGasSupply_07.png | Bin 19227 -> 27649 bytes 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.../publishedExamples/runProtonicCell_11.png | Bin 24420 -> 24420 bytes .../publishedExamples/runProtonicCell_12.png | Bin 25119 -> 25119 bytes .../publishedExamples/runProtonicCell_13.png | Bin 25834 -> 25834 bytes .../runProtonicCell_source.rst | 2 +- .../publishedExamples/runProtonicMembrane.png | Bin 3113 -> 1350 bytes .../publishedExamples/runProtonicMembrane.rst | 154 ++++++++++++++---- .../runProtonicMembrane_01.png | Bin 15091 -> 26512 bytes .../runProtonicMembrane_02.png | Bin 14828 -> 26026 bytes .../runProtonicMembrane_03.png | Bin 15400 -> 27709 bytes .../runProtonicMembrane_04.png | Bin 15252 -> 27721 bytes .../runProtonicMembrane_05.png | Bin 15586 -> 37201 bytes .../runProtonicMembrane_06.png | Bin 14023 -> 26838 bytes .../runProtonicMembrane_07.png | Bin 20147 -> 32378 bytes .../runProtonicMembrane_source.rst | 120 +++++++++++--- Documentation/utils/publishExamplesXML.m | 13 +- ProtonicMembrane/examples/runProtonicCell.m | 2 +- 42 files changed, 233 insertions(+), 60 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a/Documentation/publishedExamples/runProtonicCell.png b/Documentation/publishedExamples/runProtonicCell.png index 30b46110e55a136b97b4fb6a3b5b9c96b230391e..9e44a0b895cdc741883eba7056b370e94b48a73e 100644 GIT binary patch delta 18 ZcmZqTY~q}t%g!s$@@~0%&_)wK7639K1#kcW delta 18 ZcmZqTY~q}t%g&?C6E!7l!A2857631i1vvl! diff --git a/Documentation/publishedExamples/runProtonicCell.rst b/Documentation/publishedExamples/runProtonicCell.rst index d4b76cd1..249bb3de 100644 --- a/Documentation/publishedExamples/runProtonicCell.rst +++ b/Documentation/publishedExamples/runProtonicCell.rst @@ -120,7 +120,7 @@ we plot the inlet faces .. code-block:: matlab figure('position', [337, 757, 3068, 557]) - plotGrid(model.Electrolyser.grid, 'facecolor', 'none', 'edgecolor', 'none') + plotGrid(model.Electrolyser.grid, 'facecolor', 'red', 'edgecolor', 'none') plotGrid(model.GasSupply.grid, 'facecolor', 'none', 'edgealpha', 0.2) plotFaces(model.GasSupply.grid, model.GasSupply.couplingTerms{1}.couplingfaces, 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:battmofile:`1d-PM-geometry.json` .. code-block:: matlab @@ -30,10 +30,13 @@ We setup the input parameter structure which will we be used to instantiate the .. code-block:: matlab - inputparams = ProtonicMembraneCellInputParams(jsonstruct); - - % We setup the grid, which is done by calling the function :battmo:`setupProtonicMembraneCellGrid` - [inputparams, gen] = setupProtonicMembraneCellGrid(inputparams, jsonstruct); + inputparams = ProtonicMembraneInputParams(jsonstruct); + +We setup the grid, which is done by calling the function :battmo:`setupProtonicMembraneGrid` + +.. code-block:: matlab + + [inputparams, gen] = setupProtonicMembraneGrid(inputparams, jsonstruct); Model setup @@ -42,7 +45,7 @@ We instantiate the model for the protonic membrane cell .. code-block:: matlab - model = ProtonicMembraneCell(inputparams); + model = ProtonicMembrane(inputparams); The model is equipped for simulation using the following command (this step may become unnecessary in future versions) @@ -60,20 +63,14 @@ We setup the initial state using a default setup included in the model state0 = model.setupInitialState(); -Schedule schedule -================= -We setup the schedule, which means the timesteps and also the control we want to use. In this case we use current control and the current equal to zero (see here :battmofile:`here`). -We compute the steady-state solution so that the time stepping here is more an artifact to reach the steady-state solution. In particular, it governs the pace at which we increase the non-linearity (not detailed here). - -.. code-block:: matlab - - schedule = model.Control.setupSchedule(inputparams.jsonstruct); - -We change the default tolerance +Schedule +======== +We setup the schedule, which means the timesteps and also the control we want to use. In this case we use current control and the current equal to zero (see :battmofile:`here `). +We compute the steady-state solution and the time stepping here does not correspond to time values but should be seen as step-wise increase of the effect of the non-linearity (in particular in the expression of the conductivity which includes highly nonlineaer effect with the exponential terms. We do not detail here the method). .. code-block:: matlab - model.nonlinearTolerance = 1e-8; + schedule = model.Control.setupSchedule(jsonstruct); Simulation @@ -87,7 +84,7 @@ We run the simulation Plotting ======== -We setup som shortcuts for convenience +We setup som shortcuts for convenience and introduce plotting options .. code-block:: matlab @@ -105,47 +102,142 @@ We recover the position of the mesh cell of the discretization grid. This is use xc = model.(elyte).grid.cells.centroids(:, 1); -We consider the solution obtained at the last time step, which corresponds to the solution at steady-state. +We consider the solution obtained at the last time step, which corresponds to the solution at steady-state. The second line adds to the state variable all the variables that are derived from our primary unknowns. .. code-block:: matlab state = states{end}; state = model.addVariables(state, schedule.control); - - figure(1) + +Plot of electromotive potential + +.. code-block:: matlab + + figure plot(xc, state.(elyte).pi) title('Electromotive potential (\pi)') xlabel('x / m') ylabel('\pi / V') - - figure(2) + +.. figure:: runProtonicMembrane_01.png + :figwidth: 100% + +Plot of electronic chemical potential + +.. code-block:: matlab + + figure plot(xc, state.(elyte).pi - state.(elyte).phi) title('Electronic chemical potential (E)') xlabel('x / m') ylabel('E / V') - - figure(3) + +.. figure:: runProtonicMembrane_02.png + :figwidth: 100% + +Plot of electrostatic potential + +.. code-block:: matlab + + figure plot(xc, state.(elyte).phi) title('Electrostatic potential (\phi)') xlabel('x / m') ylabel('\phi / V') - - figure(4) + +.. figure:: runProtonicMembrane_03.png + :figwidth: 100% + +Plot of the conductivity + +.. code-block:: matlab + + figure plot(xc, log(state.(elyte).sigmaEl)) title('logarithm of conductivity (\sigma)') xlabel('x / m') xlabel('log(\sigma/Siemens)') -.. figure:: runProtonicMembrane_01.png +.. figure:: runProtonicMembrane_04.png :figwidth: 100% -.. figure:: runProtonicMembrane_02.png + +Evolution of the Faradic efficiency +=================================== +We increase the current density from 0 to 1 A/cm^2 and plot the faraday efficiency. +We sample the current value from 0 to 1 A/cm^2. + +.. code-block:: matlab + + Is = linspace(0, 1*ampere/((centi*meter)^2), 20); + +We run the simulation for each current value and collect the results in the :code:`endstates`. + +.. code-block:: matlab + + endstates = {}; + for iI = 1 : numel(Is) + + model.Control.I = Is(iI); + [~, states, report] = simulateScheduleAD(state0, model, schedule); + + state = states{end}; + state = model.addVariables(state, schedule.control); + + endstates{iI} = state; + + end + +We plot the profile of the electromotive potential for the mininum and maximum current values. + +.. code-block:: matlab + + figure + hold on + + unit = ampere/((centi*meter)^2); % shortcut + + state = endstates{1}; + plot(xc, state.(elyte).pi, 'displayname', sprintf('I=%g A/cm^2', Is(1)/unit)); + state = endstates{end}; + plot(xc, state.(elyte).pi, 'displayname', sprintf('I=%g A/cm^2', Is(end)/unit)); + + title('Electromotive potential (\pi)') + xlabel('x / m') + ylabel('\pi / V') + legend + +.. figure:: runProtonicMembrane_05.png :figwidth: 100% -.. figure:: runProtonicMembrane_03.png +We retrieve and plot the cell potential + +.. code-block:: matlab + + E = cellfun(@(state) state.(an).pi - state.(ct).pi, endstates); + + figure + plot(Is/unit, E, '*-'); + xlabel('Current density / A/cm^2') + ylabel('E / V') + title('Cell potential'); + +.. figure:: runProtonicMembrane_06.png :figwidth: 100% -.. figure:: runProtonicMembrane_04.png +We retrieve and plot the Faradic efficiency + +.. code-block:: 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Load and parse input from given json files - % The source of the json files can be seen in :battmofile:`protonicMembrane` and + % The source of the json files can be seen in :battmofile:`protonicMembrane.json` and % :battmofile:`1d-PM-geometry.json` filename = fullfile(battmoDir(), 'ProtonicMembrane', 'jsonfiles', 'protonicMembrane.json'); @@ -26,14 +25,15 @@ Source code for runProtonicMembrane %% Input structure setup % We setup the input parameter structure which will we be used to instantiate the model - inputparams = ProtonicMembraneCellInputParams(jsonstruct); + inputparams = ProtonicMembraneInputParams(jsonstruct); - % We setup the grid, which is done by calling the function :battmo:`setupProtonicMembraneCellGrid` - [inputparams, gen] = setupProtonicMembraneCellGrid(inputparams, jsonstruct); + %% + % We setup the grid, which is done by calling the function :battmo:`setupProtonicMembraneGrid` + [inputparams, gen] = setupProtonicMembraneGrid(inputparams, jsonstruct); %% Model setup % We instantiate the model for the protonic membrane cell - model = ProtonicMembraneCell(inputparams); + model = ProtonicMembrane(inputparams); %% % The model is equipped for simulation using the following command (this step may become unnecessary in future versions) @@ -43,18 +43,15 @@ Source code for runProtonicMembrane % We setup the initial state using a default setup included in the model state0 = model.setupInitialState(); - %% Schedule schedule + %% Schedule % We setup the schedule, which means the timesteps and also the control we want to use. In this case we use current - % control and the current equal to zero (see here :battmofile:`here`). + % control and the current equal to zero (see :battmofile:`here `). % - % We compute the steady-state solution so that the time stepping here is more an artifact to reach the steady-state - % solution. In particular, it governs the pace at which we increase the non-linearity (not detailed here). - - schedule = model.Control.setupSchedule(inputparams.jsonstruct); + % We compute the steady-state solution and the time stepping here does not correspond to time values but should be seen + % as step-wise increase of the effect of the non-linearity (in particular in the expression of the conductivity which + % includes highly nonlineaer effect with the exponential terms. We do not detail here the method). - %% - % We change the default tolerance - model.nonlinearTolerance = 1e-8; + schedule = model.Control.setupSchedule(jsonstruct); %% Simulation % We run the simulation @@ -65,7 +62,7 @@ Source code for runProtonicMembrane % %% - % We setup som shortcuts for convenience + % We setup som shortcuts for convenience and introduce plotting options an = 'Anode'; ct = 'Cathode'; elyte = 'Electrolyte'; @@ -80,34 +77,115 @@ Source code for runProtonicMembrane xc = model.(elyte).grid.cells.centroids(:, 1); %% - % We consider the solution obtained at the last time step, which corresponds to the solution at steady-state. + % We consider the solution obtained at the last time step, which corresponds to the solution at steady-state. The second + % line adds to the state variable all the variables that are derived from our primary unknowns. state = states{end}; state = model.addVariables(state, schedule.control); - figure(1) + %% + % Plot of electromotive potential + + figure plot(xc, state.(elyte).pi) title('Electromotive potential (\pi)') xlabel('x / m') ylabel('\pi / V') - figure(2) + %% + % Plot of electronic chemical potential + + figure plot(xc, state.(elyte).pi - state.(elyte).phi) title('Electronic chemical potential (E)') xlabel('x / m') ylabel('E / V') - figure(3) + %% + % Plot of electrostatic potential + + figure plot(xc, state.(elyte).phi) title('Electrostatic potential (\phi)') xlabel('x / m') ylabel('\phi / V') - figure(4) + %% + % Plot of the conductivity + + figure plot(xc, log(state.(elyte).sigmaEl)) title('logarithm of conductivity (\sigma)') xlabel('x / m') xlabel('log(\sigma/Siemens)') + %% Evolution of the Faradic efficiency + % We increase the current density from 0 to 1 A/cm^2 and plot the faraday efficiency. + % + % We sample the current value from 0 to 1 A/cm^2. + % + + Is = linspace(0, 1*ampere/((centi*meter)^2), 20); + + %% + % We run the simulation for each current value and collect the results in the :code:`endstates`. + % + endstates = {}; + for iI = 1 : numel(Is) + + model.Control.I = Is(iI); + [~, states, report] = simulateScheduleAD(state0, model, schedule); + + state = states{end}; + state = model.addVariables(state, schedule.control); + + endstates{iI} = state; + + end + + %% + % We plot the profile of the electromotive potential for the mininum and maximum current values. + % + + figure + hold on + + unit = ampere/((centi*meter)^2); % shortcut + + state = endstates{1}; + plot(xc, state.(elyte).pi, 'displayname', sprintf('I=%g A/cm^2', Is(1)/unit)); + state = endstates{end}; + plot(xc, state.(elyte).pi, 'displayname', sprintf('I=%g A/cm^2', Is(end)/unit)); + + title('Electromotive potential (\pi)') + xlabel('x / m') + ylabel('\pi / V') + legend + + %% + % We retrieve and plot the cell potential + % + + E = cellfun(@(state) state.(an).pi - state.(ct).pi, endstates); + + figure + plot(Is/unit, E, '*-'); + xlabel('Current density / A/cm^2') + ylabel('E / V') + title('Cell potential'); + + %% + % We retrieve and plot the Faradic efficiency + % + + feff = cellfun(@(state) state.(an).iHp/state.(an).i, endstates); + + figure + plot(Is/unit, feff, '*-'); + xlabel('Current density / A/cm^2') + ylabel('Faradic efficiency / -') + title('Faradic efficiency'); + + diff --git a/Documentation/utils/publishExamplesXML.m b/Documentation/utils/publishExamplesXML.m index fceeba68..13d17813 100644 --- a/Documentation/utils/publishExamplesXML.m +++ b/Documentation/utils/publishExamplesXML.m @@ -13,11 +13,14 @@ function publishExamplesXML(varargin) opt = merge_options(opt, varargin{:}); if isempty(opt.exampleNames) - exampleNames = {{'Examples', 'basic', 'battMoTutorial'} , ... - {'Examples', 'json_input', 'runJsonScript'} , ... - {'Examples', 'basic', 'runBatteryP2D'} , ... - {'Examples', 'am_standalone', 'runSEIActiveMaterial'}, ... - {'Electrolyser', 'Examples', 'runElectrolyser'}}; + exampleNames = {{'Examples', 'basic', 'battMoTutorial'} , ... + {'Examples', 'json_input', 'runJsonScript'} , ... + {'Examples', 'basic', 'runBatteryP2D'} , ... + {'Examples', 'am_standalone', 'runSEIActiveMaterial'} , ... + {'Electrolyser', 'Examples', 'runElectrolyser'} , ... + {'ProtonicMembrane', 'examples', 'runProtonicMembrane'}, ... + {'ProtonicMembrane', 'examples', 'runGasSupply'} , ... + {'ProtonicMembrane', 'examples', 'runProtonicCell'}}; else exampleNames = opt.exampleNames; end diff --git a/ProtonicMembrane/examples/runProtonicCell.m b/ProtonicMembrane/examples/runProtonicCell.m index f15fd19a..f00bf63a 100644 --- a/ProtonicMembrane/examples/runProtonicCell.m +++ b/ProtonicMembrane/examples/runProtonicCell.m @@ -97,7 +97,7 @@ %% % we plot the inlet faces figure('position', [337, 757, 3068, 557]) -plotGrid(model.Electrolyser.grid, 'facecolor', 'none', 'edgecolor', 'none') +plotGrid(model.Electrolyser.grid, 'facecolor', 'red', 'edgecolor', 'none') plotGrid(model.GasSupply.grid, 'facecolor', 'none', 'edgealpha', 0.2) plotFaces(model.GasSupply.grid, model.GasSupply.couplingTerms{1}.couplingfaces, opts{:}); %%